J Korean Soc Med Inform.  1997 Dec;3(2):201-206.

Using Stochastic Simulation Model Vaccine Effectiveness

Affiliations
  • 1College of Nrusing, Seoul National University, Korea.
  • 2Health Computer Sciences, University of Minnesota, Minneapolis, MN, USA.
  • 3Department of Health, State of Minnesota, Minneapolis, MN, USA.

Abstract

Several measures for vaccine effectiveness have been proposed which go beyond the direct effectiveness measurement which measures the benefit of vaccination to the recipient. In this study, a Micropopulation, Monte-Carlo model of nursing home outbreaks was used to evaluate the different vaccine measures. Simulation sets at five different vaccination levels: 0%. :5%. 50%, 75% and 100% vaccinated were run. Each simulation set was a 1000 outbreaks at a medium influenza level of .08 and an underlying vaccine efficacy of .5. The indirect measures show clearly how the population benefits as the percentage of vaccination increases. The average vaccine effectiveness measure, which compares the vaccinated attack rate with what would have been expected had no vaccine been given, showed a vaccine effectiveness of .540 at 25% vaccination; .759 at 50% vaccination: .866 at 75% vaccination; and .925 at 100% vaccination. These experiments show the usefu1ness of simulation models in presenting interrelated complex information in an understandable format.

Keyword

Monte Carlo Model; Nursing Home Influenza Model; Vaccine Effectiveness; Vaccine Efficacy; Simulation

MeSH Terms

Disease Outbreaks
Influenza, Human
Nursing Homes
Vaccination
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